基于双目视觉去除附着噪声的改进算法

doi:10.3969/j.issn.1006-2475.2023.06.011

计算机与现代化 ›› 2023, Vol. 0 ›› Issue (06): 62-68.doi: 10.3969/j.issn.1006-2475.2023.06.011

基于双目视觉去除附着噪声的改进算法

彭明康, 冯成德

四川大学机械工程学院,四川成都 610065

收稿日期:2022-05-08 修回日期:2022-08-28 出版日期:2023-06-28 发布日期:2023-06-28
通讯作者: 冯成德（1962—）,男,江苏启东人,副教授,硕士,研究方向：机器视觉,数字图像处理,E-mail： fcd98@sina.com。
作者简介:彭明康（1997—）,男,四川达州人,硕士研究生,研究方向：机器视觉,E-mail： 1286636089@qq.com。
基金资助:
四川省科技计划项目（重点研发项目）（2020YFN0010）

An Improved Algorithm of Removing Adherent Noise Based on Binocular Vision

PENG Ming-kang, FENG Cheng-de

School of Mechanical Engineering, Sichuan University, Sichuan 610065, China

Received:2022-05-08 Revised:2022-08-28 Online:2023-06-28 Published:2023-06-28

摘要/Abstract

摘要： 为去除因镜头或保护镜面上的附着物引起的图像噪声,提出一种基于双目视觉的快速去噪算法。首先通过引入分步匹配与积分图,实现实际视差图的快速计算。其次,利用双目相机与附着物所在镜面的间距计算附着噪声的理论视差,并结合实际视差图完成噪声定位。接着利用图像修复对噪声区域视差进行估计,得到被附着噪声所遮挡像素的视差。最后针对左图噪声像素,利用估计视差找到右图对应干净像素并替换,完成附着噪声去除。实验对比本文算法与现有的基于双目视觉去噪算法,结果表明,该算法在保证较好去噪效果的同时,去噪速度得到显著提升。本文方法对比学习类去噪算法,具有去噪效果稳定,不易误识别的优势。

关键词: 附着噪声, 双目视觉, 分步匹配, 积分图像

Abstract: In order to remove the image noise caused by the attachments on the lens or protective glass, a fast denoising algorithm based on binocular vision is proposed. Firstly, by introducing the step-by-step matching and integral map, the fast calculation of the real disparity map is realized. Secondly, the theoretical disparity of the attached noise is calculated by using the distance between the binocular camera and the glass where the attachment is located, and the noise localization is completed in combination with the actual disparity map. Then, image inpainting is used to estimate the disparities of the noise area, and the disparities of the pixels occluded by the attached noise is obtained. Finally, for the noise pixels in the left image, the estimated disparity is used to find the corresponding clean pixels in the right image and replace them to complete the removal of attached noise. The experiment compares the algorithm with the existing binocular vision-based denoising algorithm, and the results show that the algorithm can significantly improve the denoising speed while ensuring similar denoising effect. Compared with the learning-based denoising algorithm, this method has the advantages of stable denoising effect and will not identify other areas as noise.

Key words: adherent noise, binocular vision, step by step matching, integral image

中图分类号:

TP391.4

彭明康, 冯成德. 基于双目视觉去除附着噪声的改进算法[J]. 计算机与现代化, 2023, 0(06): 62-68.

PENG Ming-kang, FENG Cheng-de. An Improved Algorithm of Removing Adherent Noise Based on Binocular Vision[J]. Computer and Modernization, 2023, 0(06): 62-68.

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基于双目视觉去除附着噪声的改进算法

An Improved Algorithm of Removing Adherent Noise Based on Binocular Vision

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